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Open AccessArticle

A Performance Evaluation of Two Bispectrum Analysis Methods Applied to Electrical Current Signals for Monitoring Induction Motor-Driven Systems

1
School of Industrial Automation, Beijing Institute of Technology, Zhuhai 519088, China
2
Department of Mechanical, Aerospace and Civil Engineering, Brunel University London, Uxbridge, Middlesex UB8 3PH, UK
3
Centre for Efficiency and Performance Engineering, University of Huddersfield, Huddersfield HD1 3DH, UK
4
School of Engineering, University of Bolton, Bolton BL3 5AB, UK
5
School of Mechanical Engineering, Xi’an Jiaotong University, Xi’an 710049, China
*
Authors to whom correspondence should be addressed.
Energies 2019, 12(8), 1438; https://doi.org/10.3390/en12081438
Received: 3 March 2019 / Revised: 29 March 2019 / Accepted: 9 April 2019 / Published: 15 April 2019
(This article belongs to the Special Issue Fault Diagnosis in Electric Motors)
This paper investigates the performance of the conventional bispectrum (CB) method and its new variant, the modulation signal bispectrum (MSB) method, in analysing the electrical current signals of induction machines for the condition monitoring of rotor systems driven by electrical motors. Current signal models which include the phases of the various electrical and magnetic quantities are explained first to show the theoretical relationships of spectral sidebands and their associated phases due to rotor faults. It then discusses the inefficiency of CB and the proficiency of MSB in characterising the sidebands based on simulated signals. Finally, these two methods are applied to analyse current signals measured from different rotor faults, including broken rotor bar (BRB), downstream gearbox wear progressions and various compressor faults, and the diagnostic results show that the MSB outperforms the CB method significantly in that it provides more accurate and sparse diagnostics, thanks to its unique capability of nonlinear modulation detection and random noise suppression. View Full-Text
Keywords: modulation signal bispectrum; higher order spectra; fault diagnosis; induction motor; gearbox; reciprocating compressor modulation signal bispectrum; higher order spectra; fault diagnosis; induction motor; gearbox; reciprocating compressor
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Huang, B.; Feng, G.; Tang, X.; Gu, J.X.; Xu, G.; Cattley, R.; Gu, F.; Ball, A.D. A Performance Evaluation of Two Bispectrum Analysis Methods Applied to Electrical Current Signals for Monitoring Induction Motor-Driven Systems. Energies 2019, 12, 1438.

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